Description Usage Arguments Value Note Author(s)
Estimation of σ using a two layer estimation scheme as in Refitted Cross Validation, by performing variable selection with the Quantile Universal Threshold, and obtaining the two estimations of sigma with the ordinary least squares estimator.
1 2 3 |
y |
response variable. Quantitative for family= |
X |
input matrix, of dimension n x p; each row is an observation vector. |
estimator |
type of estimation of sigma when |
intercept |
should intercept(s) be fitted (default=TRUE) or set to zero (FALSE). |
alpha.level |
level, such that quantile τ=(1- |
M |
number of Monte Carlo Simulations to estimate the distribution Λ. Default is 1000. |
qut.standardize |
standardize matrix X with a quantile-based standardization. Default is TRUE. |
penalty.factor |
separate penalty factors can be applied to each coefficient. As in |
offset |
a vector of length |
... |
other |
Estimator of σ
lambdaqut
,qut
Jairo Diaz
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.